Why are some programming languages better for certain types of projects than other programming languages, when they can all essentially do the same thing and they all seem to work the same way?
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Programming languages can be specialized to do certain things, even if they all appear to potentially do the same thing.
R is a relatively simple language. Sure, you can generate *some* graphics in it, but you will not be able to really build a game. R is data analysis-focused by and large.
While I could do neural networks in R it is not ideal. It is very hard to code and extremely slow. Python comes in for it being easy to produce code for and being more of a general programming language which people tend to write predictive system packages in
A language like Delphi is great for graphics to build applications, but not so ideal for analysis you’d do in R.
On the flip side, there is MatLab which can do things like R (and sometimes more advanced) but it is 1. Locked behind a paywall 2. Not as simple of a language to learn. SPSS is great for its point-and-click interface, but its syntax backend leaves a lot to be desired. And, like MatLab, it too is locked behind a paywall.
The general consensus is that if you get really good at coding in one language, then probably stick to that language especially if it is widely used in your industry. Some languages just do certain jobs more efficiently. For example, I had to translate the command to remove outliers from Excel into R which was pretty hard…but Excel already has it built in and I needed it included in my R script for other analyses.
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